1. INFO 4990: Research Methods DECO3008: BDesComp Prep Honours Overview (March 2005) Lecture by Mary Lou Maher based in part on materials by A. Fekete, J. Davis and others

2. Research Key components –A question of interest –A claim –Evidence –Argument (link evidence to claim) What are some of the different kinds of research?

3. Definition of Research As a general term, research is gathering information that answers a question and so solves a problem. from Booth, Colomb, & Williams “The Craft of Research” Eg journalist finds out who contributed to election campaign fund, to understand political decisions Eg repairer finds out what procedure to use to fix a washing machine

4. Academic Research In academic research, you must not only answer a question, but you must find something new and interesting. You join a community of researchers. –You must advance the collective understanding of this community. Each community has a cumulative tradition with a set of interesting questions, tools and methods, practices, a style and language for writing up the research. –Research is a conversation and ongoing social activity! You need critical and careful reading of published research –to learn what the community already knows –to fit your work into the community –to be prepared for your own work to be evaluated

5. A question Every piece of research should address a question of interest to the community Each community has a tradition of style of question, –what happens? –why does it happen? –how should one do something? –what something should one do? Many questions fit into an on-going agenda –eg find data models to represent different sorts of information –eg move data and computation in a network to exploit locality

6. A claim Every piece of research makes a claim (the “contribution”) –this should answer a question of interest Claims can be very diverse, among fields and within fields This is what happens –eg how often is data corrupted when using weak concurrency control This is why something happens –eg what factors lead to project success in open-source development This is a better way to do something –eg efficiently recalculate a graph layout after a change to topology This is a better something to do –eg allow users to see the model of their skills kept in a teaching system Be explicit about the meaning of “better”

7. Evidence You must back up the claim with evidence –examples a prototype implementation to show that a system can be built to achieve claimed functionality a simulation model which is executed to show a system has certain properties measurements of a running system to show it has good performance observations of behaviour in an organisation to show what is happening a mathematical proof to show that some process has desired properties Each research method is defined by the sort of evidence that it can produce –each community has its own standards of quality and reasonableness

8. Argument You should show that the evidence you offer supports the claim you made –It’s essential that you deal with natural or obvious objections to the correctness or importance of the work –that is, you must think like your readers, and anticipate their reactions In systems work, this is often called an “evaluation” of the design

9. Some types of claim and argument This system design leads to better performance on some metric –make sure you limit how much worse this makes other metrics (such as cost!) –make sure your measurements are fair (don’t compare with “strawman” design but with state-of-the-art) This system design offers better functionality for some uses –make sure you show it can be implemented with adequate performance

10. Some types of claim and argument This behaviour can be explained by this theory –make sure you don’t have confounding factors such as level of experience, or method novelty, or subject expectations (“placebo effect”) This is what happens –make sure you don’t interfere too much with what happens when you gather data, or misinterpret it due to observer expectations

11. Common mistakes I Gather lots of data without a focussed question or method A collection of facts is not a contribution! –it must reveal some pattern or understanding that you make explicit

12. Common mistakes II Build a system without a focused question or planned evaluation –eg let’s see how to use aspect-oriented programming in a sensor network An innovative system is not a contribution! –it must be a worthwhile innovation in a sense you make explicit eg better performance eg new functionality

13. Negative results Sometimes, you don’t get the result you hoped for –You gather data that does not reveal any pattern or understanding eg no factor seems to correlate well with project success –You design a system that turns out to be worse than the state-of-the- art eg your machine learning algorithm runs slower than expected You can still salvage a thesis –Try to find some way to contribute to our understanding, or suggest fruitful directions for further work eg what features of the algorithm make it slow –Make sure the problem is intrinsic, not just your bad coding/experiment design/etc

14. Ground-breaking work Very rarely, a piece of research will establish a whole new agenda for a field, or even a new field –the contribution can be as much in the possibilities for further work, as in the result itself! In some sense, this is work that asks a new type of question, or introduces a new method I don’t recommend this for Hons/MIT/MSc/PhD –save the idea till you have time enough, and flexibility enough to deal with inevitable digressions/difficulties

15. Great scholars do not solve problems; they create them. -Albert Einstein

16. Idealised Research Process Claim: Find a “Question” to seek an answer for and anticipate the answer Method: Choose an appropriate research method and make flexible plans Evidence: Gather the data, do the experiment, build the prototype etc. Contribution: Analyse, interpret, and conclude Argument: Write the report –Importance of “writing” (aided by thinking from the point of view of your readers)

17. Actual Research Process Research explores new areas and the results are not predictable The research plan is iterative –Developing the argument leads to changes in the claim –Gathering evidence leads to changes to the claim sometimes one refines the claim –eg limit the scope (from “this has higher throughput” to “this has higher throughput if the contention rate is low”) sometimes one must change the claim entirely sometimes while gathering evidence, one finds new questions which look worth answering! New claims or questions need further evidence, revised plans, maybe even different methods

18. Finding a Question Especially when you are learning to do research, it may be already chosen for you by supervisor –or supervisor may suggest an area, and leave you to find the question A question may arise from some previous research –Further work, issues not addressed, holes in the evidence collected A question may come from the combination of previous research –Bring two areas together, use a technique from one area in another A question may arise due to new technology –new hardware or technique may require new models, new hardware may influence use or performance or feasibility A question may come from first principles

19. Suitable Research Questions Specificity and answerability– can the questions be answered through research? Scale: Consider available resources (equipment, time, skills) Scope: Often start with broad topic space, then narrow in to a specific question

20. Defining the Research Problem You need several clear, concise and succinct statements of the research problem of different lengths –eg one minute (elevator) pitch –eg ten minutes introduction to full seminar Issues you must deal with: –Can it be understood by others without too much background? –Does it demonstrate a good understanding of the research community?